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README.md
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@@ -73,6 +73,7 @@ AstroLLaMA-2-70B-Base_AIC demonstrates notable improvements over its baseline LL
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| Model | Score (%) |
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|-------|-----------|
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| **<span style="color:green">AstroLLaMA-2-70B-Base (AstroMLab)</span>** | **<span style="color:green">76.0</span>** |
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| LLaMA-3.1-8B | 73.7 |
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| LLaMA-2-70B | 70.7 |
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@@ -95,5 +96,20 @@ While this model is designed for scientific use, users should be mindful of pote
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If you use this model in your research, please cite:
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```
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```
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| Model | Score (%) |
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|-------|-----------|
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| **AstroSage-LLaMA-3.1-8B (AstroMLab)** | **80.9** |
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| **<span style="color:green">AstroLLaMA-2-70B-Base (AstroMLab)</span>** | **<span style="color:green">76.0</span>** |
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| LLaMA-3.1-8B | 73.7 |
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| LLaMA-2-70B | 70.7 |
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If you use this model in your research, please cite:
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```
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@ARTICLE{2024arXiv240919750P,
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author = {{Pan}, Rui and {Dung Nguyen}, Tuan and {Arora}, Hardik and {Accomazzi}, Alberto and {Ghosal}, Tirthankar and {Ting}, Yuan-Sen},
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title = "{AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomy}",
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journal = {arXiv e-prints},
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keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Computation and Language},
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year = 2024,
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month = sep,
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eid = {arXiv:2409.19750},
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pages = {arXiv:2409.19750},
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doi = {10.48550/arXiv.2409.19750},
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archivePrefix = {arXiv},
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eprint = {2409.19750},
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primaryClass = {astro-ph.IM},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2024arXiv240919750P},
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adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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```
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